超越友谊和追随者:维基百科社交网络

Johanna Geiß, Andreas Spitz, Michael Gertz
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引用次数: 14

摘要

大多数传统的社交网络依赖于用户、他们的朋友和追随者之间明确给定的关系。在本文中,我们超越了结构良好的数据存储库,并从非结构化文本中创建了一个以人为中心的网络——维基百科社交网络。为了识别维基百科中的人,我们使用维基间链接、维基百科分类和维基数据中提供的与人相关的信息。从维基百科页面上的人的共同出现中,我们构建了一个大规模的以人为中心的网络,并根据他们在文本中提到的距离为两个人的关系提供了一个加权方案。我们提取了网络的关键特征,如中心性、聚类系数和组件大小,我们找到了社会网络的典型值。使用最先进的算法在大规模网络中进行社区检测,我们识别出有趣的社区,并根据维基百科的分类对它们进行评估。以这种方式开发的维基百科社交网络为未来的社会分析任务提供了重要的来源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Beyond friendships and followers: The Wikipedia social network
Most traditional social networks rely on explicitly given relations between users, their friends and followers. In this paper, we go beyond well structured data repositories and create a person-centric network from unstructured text - the Wikipedia Social Network. To identify persons in Wikipedia, we make use of interwiki links, Wikipedia categories and person related information available in Wikidata. From the co-occurrences of persons on a Wikipedia page we construct a large-scale person-centric network and provide a weighting scheme for the relationship of two persons based on the distances of their mentions within the text. We extract key characteristics of the network such as centrality, clustering coefficient and component sizes for which we find values that are typical for social networks. Using state-of-the-art algorithms for community detection in massive networks, we identify interesting communities and evaluate them against Wikipedia categories. The Wikipedia social network developed this way provides an important source for future social analysis tasks.
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